Question about ACT behavior when object is absent or significantly displaced

Hi, thank you for sharing this excellent work. The method is impressive, and the codebase is very helpful for reproducing and adapting ACT-style policies to real robot tasks.

I am currently using Leju 4Pro with a Qiangnao dexterous hand to train an ACT policy. The task is to grasp an object and place it into a box.

After training, the policy can complete the full task when the object is placed in the demonstrated region. However, I noticed that when the object is moved too far away from the training distribution, or when the object is completely removed from the scene, the policy still executes almost the same grasping and placing motion.

I would like to ask:

1、Is this expected behavior for ACT when the training data mainly contains successful demonstrations?
2、Would you recommend adding negative demonstrations, such as “no object → stay still” or “object too far → do not execute”?
3、Is there a recommended way to make the policy more sensitive to object presence and position, for example by adding object detection, failure cases, or additional observation/reward signals?
4、In your experience, is this mainly caused by overfitting to the demonstrated action trajectory, insufficient visual conditioning, or lack of out-of-distribution data?

No files, tests, or entry points are named. Start by reviewing the ACT policy's observation and training-data handling in the repository, focusing on behavior when the object is absent or displaced. Done means determining whether the behavior is expected and documenting evidence-based recommendations about demonstrations, visual conditioning, and out-of-distribution cases.